Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/populism_model236 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/populism_model236 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/populism_model236")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/populism_model236") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/populism_model236", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9f84d9ca539deb082c1980d8b7a285682a099a25413cabf40df3778c63e5823
- Size of remote file:
- 5.37 kB
- SHA256:
- b2a64eaf63be33e86b216c5bf4f4333fab6b910201cf961d16b42ba0f68967ec
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